nipype.interfaces.dipy.tensors module

class nipype.interfaces.dipy.tensors.DTI(check_import=True, *args, **kwargs)

Bases: DipyDiffusionInterface

Calculates the diffusion tensor model parameters

Example

>>> import nipype.interfaces.dipy as dipy
>>> dti = dipy.DTI()
>>> dti.inputs.in_file = 'diffusion.nii'
>>> dti.inputs.in_bvec = 'bvecs'
>>> dti.inputs.in_bval = 'bvals'
>>> dti.run()

Mandatory Inputs

in_bvala pathlike object or string representing an existing file

Input b-values table.

in_bveca pathlike object or string representing an existing file

Input b-vectors table.

in_filea pathlike object or string representing an existing file

Input diffusion data.

Optional Inputs

b0_thresan integer

B0 threshold. (Nipype default value: 700)

mask_filea pathlike object or string representing an existing file

An optional white matter mask.

out_prefixa string

Output prefix for file names.

Outputs

ad_file : a pathlike object or string representing an existing file color_fa_file : a pathlike object or string representing an existing file fa_file : a pathlike object or string representing an existing file md_file : a pathlike object or string representing an existing file out_file : a pathlike object or string representing an existing file rd_file : a pathlike object or string representing an existing file

class nipype.interfaces.dipy.tensors.TensorMode(check_import=True, *args, **kwargs)

Bases: DipyDiffusionInterface

Creates a map of the mode of the diffusion tensors given a set of diffusion-weighted images, as well as their associated b-values and b-vectors [1]. Fits the diffusion tensors and calculates tensor mode with Dipy.

Example

>>> import nipype.interfaces.dipy as dipy
>>> mode = dipy.TensorMode()
>>> mode.inputs.in_file = 'diffusion.nii'
>>> mode.inputs.in_bvec = 'bvecs'
>>> mode.inputs.in_bval = 'bvals'
>>> mode.run()

References

Mandatory Inputs

in_bvala pathlike object or string representing an existing file

Input b-values table.

in_bveca pathlike object or string representing an existing file

Input b-vectors table.

in_filea pathlike object or string representing an existing file

Input diffusion data.

Optional Inputs

b0_thresan integer

B0 threshold. (Nipype default value: 700)

mask_filea pathlike object or string representing an existing file

An optional white matter mask.

out_prefixa string

Output prefix for file names.

Outputs

out_file : a pathlike object or string representing an existing file